Paper Citation Record · LEDGER

Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2407.16833.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2407.16833 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:31:49.682406Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-25T06:26:41.320119Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b9e4393a-a825-4167-8602-22ae438c1dc0 · inbound

From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation cites this paper.

From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-09T19:31:49.682406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5662039a-e072-439e-866d-c89b879a0ff1 · inbound

Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation cites this paper.

Speculative Prefill: Turbocharging TTFT with Lightweight and Training-Free Token Importance Estimation Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T11:11:17.726660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e676f44-8e09-4344-81a7-55f058cf3c0a · inbound

Syntriever: How to Train Your Retriever with Synthetic Data from LLMs cites this paper.

Syntriever: How to Train Your Retriever with Synthetic Data from LLMs Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T00:40:42.540354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 200436e0-c38a-481b-b8d5-7720a19bba5d · inbound

QwenLong-CPRS: Towards $\infty$-LLMs with Dynamic Context Optimization cites this paper.

QwenLong-CPRS: Towards $\infty$-LLMs with Dynamic Context Optimization Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:40:53.253318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a1dbcc6-80eb-48ee-a43c-b3dcefd75410 · inbound

LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework cites this paper.

LOOM-Scope: a comprehensive and efficient LOng-cOntext Model evaluation framework Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T19:45:12.486670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dbc1ccd-d00e-4789-886e-992c8c8dede8 · inbound

Exploring Robust Multi-Agent Workflows for Environmental Data Management cites this paper.

Exploring Robust Multi-Agent Workflows for Environmental Data Management Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T16:57:53.479552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fbaece3-90a3-4b74-b4af-5634ab826fbf · inbound

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure cites this paper.

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:26:00.827615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9239c8f8-4afe-4a16-a949-44ffdcfee01e · inbound

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure cites this paper.

Retrieval Is Not Enough: Why Organizational AI Needs Epistemic Infrastructure Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:26:41.323785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.